Alberto Rosi

Extracting urban patterns from location-based social networks

Social networks attract lots of new users every day and absorb from them information about events and facts happening in the real world. The exploitation of this information can help identifying mobility patterns that occur in an urban environment as well as produce services to take advantage of social commonalities between people. In this paper we set out to address the problem of extracting urban patterns from fragments of multiple and sparse people life traces, as they emerge from the participation to social network. To investigate this challenging task, we analyzed 13 millions Twitter posts (3 GB) of data in New York. Then we test upon this data a probabilistic topic models approach to automatically extract urban patterns from location-based social network data. We find that the extracted patterns can identify hotspots in the city, and recognize a number of major crowd behaviors that recur over time and space in the urban scenario.

Self-aware Pervasive Service Ecosystems

Here we present the overall objectives and approach of the SAPERE (“Self-aware Pervasive Service Ecosystems”) project, focussed on the development of a highly-innovative nature-inspired framework, suited for the decentralized deployment, execution, and management, of self-aware and adaptive pervasive services in future network scenarios.

Developing pervasive multi-agent systems with nature-inspired coordination

Pervasive computing systems can be modelled effectively as populations of interacting autonomous components. The key challenge to realizing such models is in getting separately-specified and -developed sub-systems to discover and interoperate with each other in an open and extensible way, supported by appropriate middleware services. In this paper, we argue that nature-inspired coordination models offer a promising way of addressing this challenge. We first frame the various dimensions along which nature-inspired coordination models can be defined, and survey the most relevant proposals in the area. We describe the nature-inspired coordination model developed within the SAPERE project as a synthesis of existing approaches, and show how it can effectively support the multifold requirements of modern and emerging pervasive services. We conclude by identifying what we think are the open research challenges in this area, and identify some research directions that we believe are promising.

Pervasive social context: Taxonomy and survey

As pervasive computing meets social networks, there is a fast growing research field called pervasive social computing. Applications in this area exploit the richness of information arising out of people using sensor-equipped pervasive devices in their everyday life combined with intense use of different social networking services. We call this set of information pervasive social context. We provide a taxonomy to classify pervasive social context along the dimensions space, time, people, and information source (STiPI) as well as commenting on the type and reason for creating such context. A survey of recent research shows the applicability and usefulness of the taxonomy in classifying and assessing applications and systems in the area of pervasive social computing. Finally, we present some research challenges in this area and illustrate how they affect the systems being surveyed.

Supporting location-aware services for mobile users with the whereabouts diary

Modern handheld devices provided with localization capabilities could be used to automatically create a diary of users whereabouts, and use it as a complement of the user profile in many applications. In this paper we present the Whereabouts diary, an application/service to log the places visited by the user and to label them, in an automatic way, with descriptive semantic information. In particular, Web-retrieved data and the temporal patterns in which places are visited can be used to define such meaningful semantic labels. In this paper, we describe the general idea at the basis of our service and discuss our implementation and the associated experimental results. In addition, we illustrate an application that can fruitfully exploit the whereabouts diary as a supporting service, and discuss areas for future work.

Engineering Pervasive Service Ecosystems: The SAPERE Approach

Emerging pervasive computing services will typically involve a large number of devices and service components cooperating together in an open and dynamic environment. This calls for suitable models and infrastructures promoting spontaneous, situated, and self-adaptive interactions between components. SAPERE (Self-Aware Pervasive Service Ecosystems) is a general coordination framework aimed at facilitating the decentralized and situated execution of self-organizing and self-adaptive pervasive computing services. SAPERE adopts a nature-inspired approach, in which pervasive services are modeled and deployed as autonomous individuals in an ecosystem of other services and devices, all of which interact in accord to a limited set of coordination laws, or eco-laws. In this article, we present the overall rationale underlying SAPERE and its reference architecture. We introduce the eco-laws--based coordination model and show how it can be used to express and easily enforce general-purpose self-organizing coordination patterns. The middleware infrastructure supporting the SAPERE model is presented and evaluated, and the overall advantages of SAPERE are discussed in the context of exemplary use cases.

MyAds: A system for adaptive pervasive advertisements

In this paper we show how pervasive technologies can be employed on a public-display advertisement scenario to enable behavioral self-adaptation of content. We show this through MyAds, a system capable of exploiting pervasive technologies to autonomously adapt the advertisement process to the trends of interests detected among the audience in a venue. After describing the rationale, the architecture and the prototype of MyAds, we describe the advantages brought by the use of such a system, in terms of impact on the audience and economic efficiency. The comparison of MyAds performances with different advertisement selection techniques confirms the validity of our advertisement model, and our prototype in particular, as a means for maximising product awareness in an audience and for enhancing economic efficiency.

Automatic Analysis of Geotagged Photos for Intelligent Tourist Services

Web communities are making available an increasing volume of free, fresh, detailed and powerful information about living people. Among them, the Flickr photo-sharing service offers to researchers a database of several millions of geotagged pictures from users all around the world. Working on that opens the door to the study of meaningful mobility data, where title and description of a geotagged picture represent a mine from which extract labels to detect places and events, and useful information about user trends, behaviors and tastes. Our approach goes in the direction of developing an intelligence and unattended system able to extract and take advantage of up-to-date and spontaneous information embedded with pictures, making cities intelligent and able to reach user expectations. Such system, learning from past touristic user experiences, could make customized recommendations on “where to go”, and “what to see”, to people going to visit touristic places for the first time.

Pervasive Middleware Goes Social: The SAPERE Approach

Pervasive computing middleware, to support the spatially and socially situated activities of users, has to effectively support both self-organizing spatial activities and social models of interactions. In this paper, we present the solution that we are going to integrate in the SAPERE middleware to tackle this problem. The basic idea is to exploit the graph of a social network (e.g., Face book), in conjunction with relations deriving from spatial proximity, to drive and rule the actual topology of interactions among devices, users, and services. The approach can facilitates the autonomous and adaptive activities of pervasive services while accounting for both social and spatial issues, can support effective service discovery and orchestration, and can enable tackling critical privacy issues.

The whereabouts diary

The user profile is one of the main context-information in a wide range of pervasive computing applications. Modern handheld devices provided with localization capabilities could automatically create a diary of users whereabouts and use that information as a surrogate (or a complement) of the user profile. The places we go, in fact, reveal also something about us, for example, two persons can be matched as compatible given the fact they visit the same places. Web-retrieved information, and the temporal patterns with which different places are visited, can be used to automatically define meaningful semantic labels to the visited places. In our work we used geocoding and whitepages Web-services to extract information about a place, and Bayesian networks to classify places on the basis of the time in which they have been visited. In this paper we describe the general idea at the basis of the whereabouts diary, discuss our implementation, and present experimental results. Finally, several applications that can exploit the diary are illustrated.